The Unreasonable Effectiveness of Address Clustering
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Abstract (arXiv)
Address clustering tries to construct the one-to-many mapping from entities to addresses in the Bitcoin system. Simple heuristics based on the micro-structure of transactions have proved very effective in practice. In this paper we describe the primary reasons behind this effectiveness: address reuse, avoidable merging, super-clusters with high centrality, and the incremental growth of address clusters. We quantify their impact during Bitcoin's first seven years of existence.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 May 2016.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1; 2024: 2; 2025: 0; 2026: 1.
8 papers.
- 2024The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Datasetcited by 8
- 2022Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application of Machine Learning-based Forensicscited by 5
- 2021Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networkscited by 2
- 2022Pattern Analysis of Money Flow in the Bitcoin Blockchaincited by 2
- 2024Machine Learning for Blockchain Data Analysis: Progress and Opportunitiescited by 2
- 2021Identifying Ransomware Actors in the Bitcoin Networkcited by 1
- 2023Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchaincited by 0
- 2026Refining Heuristic-Based Bitcoin Address Clustering with Graph Neural Networkscited by 0
- 2026Refining Heuristic-Based Bitcoin Address Clustering with Graph Neural Networks1 Sep 2026
- 2024The Shape of Money Laundering: Subgraph Representation Learning on the Blockchain with the Elliptic2 Dataset29 Apr 2024
- 2024Machine Learning for Blockchain Data Analysis: Progress and Opportunities28 Apr 2024
- 2023Temporal and Geographical Analysis of Real Economic Activities in the Bitcoin Blockchain17 Jul 2023
- 2022Pattern Analysis of Money Flow in the Bitcoin Blockchain15 Jul 2022
- 2022Detecting Anomalous Cryptocurrency Transactions: an AML/CFT Application of Machine Learning-based Forensics7 Jun 2022
- 2021Identifying Ransomware Actors in the Bitcoin Network28 Aug 2021
- 2021Label-GCN: An Effective Method for Adding Label Propagation to Graph Convolutional Networks5 Apr 2021